More Than Historical Data in Digital Transformation

by | Dec 2, 2019 | Digital Transformation, Industrial IoT | 0 comments

A recent Wood Mackenzie article, Digitalisation: upstream’s silver bullet?, noted:

To date, we believe there’s been far more talk than action – and little evidence of tangible change to the top or bottom lines.

I caught up with Emerson’s Jonas Berge about his thoughts after reading this report. He found the whitepaper to be quite revealing. It reveals that management consulting firms share a different vision for digital transformation.

For instance, “Big data initiatives proved costly and have failed to show material results yet…” reveals a focus on Big Data, such as building a data lake in the cloud for historical data.

Jonas notes that from a process automation standpoint, you cannot become predictive with historical data alone. You cannot get real-time dashboards with historical data. You need real-time data which comes from sensors.

Historian passes live data through to predictive analytics appsIn this article, the word “sensor” appears once. The word “wireless” does not appear at all. And, there is no mention of maintenance, reliability, or energy efficiency parts of the operations which has the savings manufacturers often focus on, but perhaps are not a focus for the those not achieving financial results in the article.

Jonas recently reviewed a digitalization project draft specification. The word “sensor” appeared only 11 times and “wireless” 3 times. This organization’s focus is on Big Data / historical data for the reservoir. They ask for reservoir model and vibration waveforms in the same data lake, which is likely not the best approach to use this data to improve business performance. Better is to start with a roadmap based on your business objectives.

Back to the article, the authors note, “…the large amount of infrastructure required mean few companies have the scale, or appetite for risk, to experiment in the development phase”. To Jonas, this again hints to costly implementation of data lakes with long implementation periods for migration of historical data, custom programming analytics, and data cleansing.

“A three-to-five-year window is simply not long enough to test, validate and implement digital technologies in the conventional space.” There are many ready-made, scalable and secure technologies Emerson provides in digital transformation initiatives to improve safety, reliability, energy & emissions, and production performance that don’t take this long to roll out and deliver business results.

One example is in plant equipment monitoring. Without real-time monitoring of assets, signs of equipment wear (e.g. bearing vibration) can eventually be seen on process variables (like discharge pressure), but the problem has likely already gone too far (e.g. bearing failure). The fastest and most reliable way to predict equipment failure is with direct equipment sensors, such as accelerometers, acoustic monitoring, and/or position, to name a few.

Jonas explained that there is still a lot of education to be done about using real-time data in digital transformation initiatives as opposed to considering the use of historical data alone. His latest essay is an attempt to widen the focus to the need for new data to solve new problems. Read more of his thoughts in his LinkedIn essay, If it won’t break, don’t sense it.

Visit the Digital Transformation section on for more on the technologies and services to help you deliver tangible results to your top and bottom lines. You can also connect and interact with other Industrial Internet of Things technology and digital transformation experts in the IIoT & Digital Transformation group in the Emerson Exchange 365 community.

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The opinions expressed here are the personal opinions of the authors. Content published here is not read or approved by Emerson before it is posted and does not necessarily represent the views and opinions of Emerson.

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